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SubjectRe: 答复: [PATCH v3] mm/compaction:let p roactive compaction order configurable
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On 5/11/21 1:48 AM, Chu,Kaiping wrote:
>
>
>> -----邮件原件-----
>> 发件人: Khalid Aziz <khalid.aziz@oracle.com>
>> 发送时间: 2021年5月7日 5:27
>> 收件人: David Rientjes <rientjes@google.com>; Chu,Kaiping
>> <chukaiping@baidu.com>
>> 抄送: mcgrof@kernel.org; keescook@chromium.org; yzaikin@google.com;
>> akpm@linux-foundation.org; vbabka@suse.cz; nigupta@nvidia.com;
>> bhe@redhat.com; iamjoonsoo.kim@lge.com; mateusznosek0@gmail.com;
>> sh_def@163.com; linux-kernel@vger.kernel.org; linux-fsdevel@vger.kernel.org;
>> linux-mm@kvack.org
>> 主题: Re: [PATCH v3] mm/compaction:let proactive compaction order
>> configurable
>>
>> On 4/25/21 9:15 PM, David Rientjes wrote:
>>> On Sun, 25 Apr 2021, chukaiping wrote:
>>>
>>>> Currently the proactive compaction order is fixed to
>>>> COMPACTION_HPAGE_ORDER(9), it's OK in most machines with lots of
>>>> normal 4KB memory, but it's too high for the machines with small
>>>> normal memory, for example the machines with most memory configured
>>>> as 1GB hugetlbfs huge pages. In these machines the max order of free
>>>> pages is often below 9, and it's always below 9 even with hard
>>>> compaction. This will lead to proactive compaction be triggered very
>>>> frequently. In these machines we only care about order of 3 or 4.
>>>> This patch export the oder to proc and let it configurable by user,
>>>> and the default value is still COMPACTION_HPAGE_ORDER.
>>>>
>>>
>>> As asked in the review of the v1 of the patch, why is this not a
>>> userspace policy decision? If you are interested in order-3 or
>>> order-4 fragmentation, for whatever reason, you could periodically
>>> check /proc/buddyinfo and manually invoke compaction on the system.
>>>
>>> In other words, why does this need to live in the kernel?
>>>
>>
>> I have struggled with this question. Fragmentation and allocation stalls are
>> significant issues on large database systems which also happen to use memory
>> in similar ways (90+% of memory is allocated as hugepages) leaving just
>> enough memory to run rest of the userspace processes. I had originally
>> proposed a kernel patch to monitor, do a trend analysis of memory usage and
>> take proactive action -
>> <https://lore.kernel.org/lkml/20190813014012.30232-1-khalid.aziz@oracle.c
>> om/>. Based upon feedback, I moved the implementation to userspace -
>> <https://github.com/oracle/memoptimizer>. Test results across multiple
>> workloads have been very good. Results from one of the workloads are in this
>> blog - <https://blogs.oracle.com/linux/anticipating-your-memory-needs>. It
>> works well from userspace but it has limited ways to influence reclamation and
>> compaction. It uses watermark_scale_factor to boost watermarks and cause
>> reclamation to kick in earlier and run longer. It uses
>> /sys/devices/system/node/node%d/compact to force compaction on the node
>> expected to reach high level of fragmentation soon. Neither of these is very
>> efficient from userspace even though they get the job done. Scaling watermark
>> has longer lasting impact than raising scanning priority in balance_pgdat()
>> temporarily. I plan to experiment with watermark_boost_factor to see if I can
>> use it in place of /sys/devices/system/node/node%d/compact and get the
>> same results. Doing all of this in the kernel can be more efficient and lessen
>> potential negative impact on the system. On the other hand, it is easier to fix
>> and update such policies in userspace although at the cost of having a
>> performance critical component live outside the kernel and thus not be active
>> on the system by default.
>>
> I studied your memoptimizer these days, I also agree to move the implementation into kernel to co-work with current proactive compaction mechanism to get higher efficiency.
> By the way I am interested about the memoptimizer, I want to have a test of it, but how to evaluate its effectiveness?
>
>

If you look at this blog I wrote on memoptimizer - <https://blogs.oracle.com/linux/anticipating-your-memory-needs>,
under the section "Measuring stalls" I describe the workload I used to measure its effectiveness. The metric I use is
number of allocation/compaction stalls over a multi-hour run of the workload. Number of allocation/compaction stalls
gives an idea of how effective system is at keeping free order 0 and larger pages available proactively. Any workload
that runs into significant number of stalls is a good workload to use to measure effectiveness.

--
Khalid

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